Authors:Henry Joutsijoki, Martti JuholaPages: 273 - 300Abstract: In this research, we examined the automated taxa identification of benthic macroinvertebrates. Benthic macroinvertebrates play an important role in biomonitoring. They can be used in water quality assessments. Identification of benthic macroinvertebrates is made usually by highly trained experts, but this approach has high costs and, hence, the automation of this identification process could reduce the costs and would make wider biomonitoring possible. The automated taxa identification of benthic macroinvertebrates returns to image classification. We applied altogether 11 different classification methods to the image dataset of eight taxonomic groups of benthic macroinvertebrates. Wide experimental tests were performed. The best results, around 94% accuracies, were achieved when quadratic discriminant analysis (QDA), radial basis function network and multi-layer perceptron (MLP) were used. On the basis of the results, it can be said that the automated taxa identification of benthic macroinvertebrates is possible with high accuracy.Keywords: benthic macroinvertebrates; classification; machine learning; water qualityCitation: International Journal of Data Science, Vol. 2, No. 4 (2017) pp. 273 - 300PubDate: 2017-11-24T23:20:50-05:00DOI: 10.1504/IJDS.2017.088101Issue No:Vol. 2, No. 4 (2017)

Authors:Tengku Adil Tengku Izhar, Torab Torabi, M. Ishaq BhattiPages: 325 - 351Abstract: Record linkage is a task of identifying data from large datasets across different data sources. Although record linkage approach has been applied in many areas, there is limited discussion on the literature that gives an overview on recent development that addressed record linkage in the scope of the organisational goals. This paper is classified according to the recent development on record linkage as an approach to drive the understanding of the dependencies of organisational data in relation to the organisational goals. We observed recent literature based on this classification to identify recent development on record linkage. The results show that there is no study in evaluating record linkage in the scope of organisational data that relate to the organisational goals. The contribution of this paper will serve as a first step to develop the dependency relationship between organisational data and organisational goals.Keywords: record linkage; data goal dependency; data linkage; organisational goals; literature reviewCitation: International Journal of Data Science, Vol. 2, No. 4 (2017) pp. 325 - 351PubDate: 2017-11-24T23:20:50-05:00DOI: 10.1504/IJDS.2017.088103Issue No:Vol. 2, No. 4 (2017)